A Multi-Set Artificial Immune System for Searching Optima in Dynamic Environments

ABSTRACT: Artificial Immune Systems (AIS) are computational methods that belong to the computational intelligence family and are inspired by the biological immune system. Many researchers developed immune based models to solve complex computational or engineering problems by using fast exploration ability of the AIS. The proposed method uses multi-set search mechanisms within AIS to solve the dynamic optimization problems, i.e. moving peak benchmarks. In the moving peak benchmark problems the optimum and environment changes in time. For this reason it is difficult to find optimum. In this thesis distributed detection and fast exploration ability of AIS are combined with multi-set search mechanisms to find optimum solutions of the given dynamic optimization problems. The given method was compared with different algorithms that solve dynamic optimization problems and the results showed that the proposed method outperforms almost all other methods. Keywords: dynamic environments, optimization problems, artificial immune systems, moving peaks benchmarks. ……………………………………………………………………………………………………………………………………………………………………………………………………………………